解读抑郁症中的社会思维:明确的信任和隐含的信念之间的计算分离,更新隐含的信念
Sara Shakeri1, Roshanak Khodabakhsh Pirkalani1
1Department of Psychology, Faculty of Education and Psychology, Alzahra University, Tehran, Iran.
Acta psychologica
|February 17, 2026
概括
抑郁症对个人如何更新对他人的可信度的信念产生负面影响,显示出对明确信任的普遍偏见,但在处理负面社会信息时具有特定背景的计算不灵活性.
科学领域:
- 计算精神病学是一种计算精神病学.
- 社会的认知社会认知.
- 神经科学是一个神经科学.
背景情况:
- 抑郁症与改变的社会认知和决策有关.
- 对于有针对性的干预措施来说,了解更新抑郁症缺陷的信念至关重要.
研究的目的:
- 调查抑郁症症状如何影响不同社会背景下关于可信度的信念更新.
- 确定抑郁症中社会认知障碍背后的计算机制.
主要方法:
- 采用计算精神病学方法,使用修改后的信任游戏.
- 评估了169名参与者在可信和不可信的合作伙伴条件下的明确信念报告和隐性计算过程.
主要成果:
- 较高的抑郁症分数预测了较低的后部信任信念,表明普遍的负面更新偏差.
- 计算建模揭示了上下文依赖的概率偏差,抑郁症状与不值得信赖的条件中的偏差减少有关.
- 只有在不值得信任的条件下,抑郁症得分与合作率下降相关.
结论:
- 研究结果揭示了抑郁症的分离:普遍的负面明确信念与特定背景的隐性偏见一起.
- 确定了对信念受损的计算标记,在抑郁症中进行更新,突出了处理负面社会证据的认知不灵活性.
- 支持理解情绪障碍的过程分离框架,并将社会认知与计算精神病学联系起来.
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